Yeying Zhu
Research interests
Dr. Zhu’s research interest lies in causal inference, machine learning and the interface between the two. She highly appreciates the interdisciplinary nature of causal inference and aim to develop theoretically sound methods for data-driven problems.
Her recent focus is on the development of variable selection/dimension reduction procedures to adjust for confounding in observational studies in a high-dimensional setting. In addition, she has developed innovative machine learning algorithms for the modeling of propensity scores for binary, multi-level and continuous treatments.Meanwhile, Dr. Zhu is also working on causal mediation analysis, which examines how a treatment/intervention affects the outcome through one/multiple intermediate variables. Applications of Dr. Zhu’s research lie in biomedical studies, public health and social sciences.
Education/biography
Professor Zhu received her BSc in Statistics at East China Normal University in 2006. Then, she went to National University of Singapore for her master degree and later, joined Penn State University in 2008. She graduated with a PhD degree in 2013. She was a pre-doctoral fellow at the Quantitative Social Science Initiative (QuaSSI) between 2010 and 2011 and a research assistant at the Penn State Methodology Center between 2011 and 2013.